ReviewToxics2026
Source, Monitoring Techniques and Prospects of Bioaerosols: A Review.
Review in Toxics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Bioaerosols play significant roles in ecological interactions, climate change, and public health. Their diverse origins contribute to a dynamic atmospheric microbiome with considerable spatiotemporal variability, which are generally categorized as natural and anthropogenic sources. Accurate monitoring and source apportionment are critical for assessing environmental impacts and health risks. This review systematically summarizes the characteristics of bioaerosol sources and emphasizes emission risks from intensive human activities. This study also elucidates source apportionment strategies of bioaerosols and analyzes the technological evolution from traditional culture-based methods to advanced molecular and real-time physicochemical systems. In addition, the shift of bioaerosol monitoring technologies towards high-sensitivity, culture-independent, and online monitoring is emphasized in this review. An outlook on future research priorities is provided in the end. We emphasize the pressing need to establish localized characteristic databases, develop integrated real-time monitoring systems coupling rapid screening with deep biological analysis, and optimize the application of machine learning and AI algorithms to enhance the precision of multi-source contribution modeling in complex environments.
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.